1. Field of the Art
This invention relates to a high-efficiency signal coding and decoding system and, particularly, to an amplitude-adaptive vector quantization system.
2. Background Technology
FIGS. 3 and 4 are block diagrams showing the coding and decoding sections, respectively, of a vector quantization system which uses the inner product for the computation of distortion. In FIG. 3, indicated by 1 is the input signal vector derived from a series of input signals divided into blocks in K-samples, 2 is a mean value separation circuit, 11 is the separated mean value, 13 is the mean separated input vector, 3 is a mean value DPCM (Differential PCM) quantizer, 29 is a vector quantizer, 31 is the amplitude gain produced through coding by the vector quantizer, 7 is an amplitude-gain DPCM quantizer, and 33 is the output vector index produced from the code of the vector quantizer. In FIG. 4, indicated by 19 is a mean value DPCM decoder, 20 is an amplitude-gain DPCM decoder, 24 is the DPCM-decoded mean value, 36 is the DPCM-decoded amplitude gain, 35 is a vector quantizing decoder, 38 is the decoded mean value separation vector, 23 is a mean value adding circuit, and 39 is the output signal vector.
Next, the operation wil be described. In the coding section of FIG. 3, the input signal vector 1 which is a series of input signals provided in the form of blocks is received by the mean value separation circuit 2 which separates the mean separated input vector 13 from the intra-vector mean value 11. The separated mean value 11 is subjected to predictive differential quantization (DPCM quantization) by the mean value DPCM quantizer 3, and information of the separated mean value 11 is reduced. The mean separated input vector 13 is subjected to inner product computation by the vector quantizer 29 with the output vector read out of a code book which is a set of output vectors prepared in advance in a statistical manner so that an output vector yielding a maximum inner product is selected. The vector quantizer 29 produces the output vector index 33 for the input mean separated input vector and also the inner product value as the amplitude gain 31 of the input mean separated input vector 13.
Vector quantization is expressed in terms of input signal vectors 13 S=S.sub.1 S.sub.2, . . . , S.sub.K, mean value .mu., amplitude gain .sigma.*, and output vectors y.sub.i =[y.sub.i1, y.sub.i2, . . . , y.sub.ik ], as follows. ##EQU1## where .sigma.=.vertline.S-.mu..U.vertline. and .vertline.yi=1 are assumed.
Using the inner product, the vector distortion computation is reduced to the form of a product-sum which is easier for execution with a DSP (digital signal processor), and the amplitude component can be obtained at the same time. The amplitude gain 31 produced by the vector quantizer 29 is subjected to DPCM quantization by the DPCM quantizer 7 in the same way as for the mean value 11.
The DPCM-quantized mean value 12, amplitude gain 32 and output vector index 33 obtained as described above are coded and then transmitted or recorded.
The decoding section of FIG. 4 implements decoding for the three components namely the DPCM-quantized mean value 12, DPCM-quantized amplitude gain 32 and output vector index 33 provided by the coding section. The DPCM-quantized mean value 12 is DPCM-decoded by the DPCM decoder 19, which yields the decoded mean value 24. Similarly, the DPCM-quantized amplitude gain 32 is DPCM-decoded by the amplitude gain DPCM decoder 20, which yields the decoded amplitude gain 36.
The vector quantization decoder 35 outputs the normalized output vector 37 by decoded the output vector index 33, the amplitude reproduction circuit 22 reproduces the amplitude of the vector as output vector 38 from the decoded amplitude gain 36, the mean value adding circuit 23 adds the decoded mean value 24 to the decoded mean separated output vector 38, and the output signal vector 39 is reproduced.
In the conventional vector quantization system using the inner product for the computation of distortion, the amplitude component is obtained after vector quantization, and therefore the vector quantization index cannot be reduced by varying the quantization stages of the tree-searched code book by the amplitude component or switching code books. If the use of inner product computation is eliminated for implementing the above-mentioned adaptive control by the amplitude component, it becomes difficult for the DSP (digital signal processor) to reduce the duty of hardware.